Job description

AZURE DATA ENGINEER

We're looking for an experienced Azure Data Engineer to join my client's fast-paced, innovative team of Data Engineers and Data Architects who work on the Microsoft Stack, predominantly Azure. Not only the owner of your own BAU workload, as our Data Engineer you'll be involved in a lot of company-wide innovative changes including migrations and your work will make an impact on millions of customers.

If you have Data Engineer commercial experience using Azure and have worked with 'Big Data' experience this may be the role for you…

About our client

A leading provider of private insurance in the UK, and the name behind several other big household insurers. Our client are going through an exciting time of digital transformation, and this role is integral to a number of business-wide changes both now and in the long-term.

Location: hybrid working, with visits at least twice a week to our client's office in Tunbridge Wells, Kent.

Competitive Salary and benefits package, based on experience

Key tasks will include but not limited to:

• Build ingestion pipelines in the cloud-based Data Lake to accommodate multiple data sources
• Interrogate and model data from multiple sources, translating into an Enterprise useable logical data model fit for Analyst consumption.
• Thorough data and understanding of business processes, advise on Analytical uses in Insight
• Provide guidance and translation to Analysts on how to interpret and navigate the data for specific use case.
• Help the Data Architect to create an overview of the Data Lineage (from data flows, data transformations inside applications to Analytical output)
• Apply Machine Learning and Automation techniques to processes within Lake helping to detect Quality issues with data.

Essential requirements:

• 2+ years working experience as a Data Engineer on Azure
• Working knowledge of Azure Data Factory, Data Lake, DataBricks and Synapse Analytics
• Working Knowledge of Power BI and providing optimised data sets that can be fully utilised by the product.
• Experience with integration of data from multiple data sources
• Machine Learning, AI and Automation techniques for Data Management & Analytics
• Awareness of Data Management best practice, including Data Lifecycle Management across Core IT & Big Data ecosystems as well as Data Privacy & Security constraints
• Experience in the following would be of benefit: Python, Spark, R , SQL, .net, Java, C++